Presentation given by Rommel N. Carvalho at the 9th International Workshop on Uncertainty Reasoning for the Semantic Web at the 12th International Semantic Web Conference in October 21, 2013, Sydney, Australia. This was a joint work between the Research and Strategic Information Directorate from Brazil's Office of the Comptroller General and the Department of Computer Science from the University of Brasília.
Title: A GUI for MLN.
Abstract: This paper focuses on the incorporation of the Markov Logic Network (MLN) formalism as a plug-in for UnBBayes, a Java framework for probabilistic reasoning based on graphical models. MLN is a formalism for probabilistic reasoning which combines the capacity of dealing with uncertainty tolerating imperfections and contradictory knowledge based a Markov Network (MN) with the expressiveness of First Order Logic. A MLN provides a compact language for specifying very large MNs and the ability to incorporate, in modular form, large domain of knowledge (expressed in First Order Logic sentences) inside itself. A Graphical User Interface for the software Tuffy was implemented into UnBBayes to facilitate the creation, and inference of MLN models. Tuffy is a Java open source MLN engine.
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A GUI for MLN
1. A GUI for MLN
Estêvão F. Aguiar, Marcelo Ladeira, Rommel N. Carvalho, and Shou
Matsumoto
Universidade de Brasília
!
Paper - Uncertainty Reasoning for the SemanticWeb
URSW - ISWC
10/21/2013 - Sydney,Australia
7. MLN
3MLN - Choice of Implementation - To GUI or Not to GUI - Conclusion
8. MLN*
4
* [Richardson & Domingos 2006]
http://hazy.cs.wisc.edu/hazy/papers/tuffy-vldb2011-slides.pdf
MLN - Choice of Implementation - To GUI or Not to GUI - Conclusion
9. MLN*
Syntax: a set of weighted logical rules
0.5 Smokes(p) => Cancer(p)
// if you smoke, you are more likely to have cancer
Weights: cost for rule violation
4
* [Richardson & Domingos 2006]
http://hazy.cs.wisc.edu/hazy/papers/tuffy-vldb2011-slides.pdf
MLN - Choice of Implementation - To GUI or Not to GUI - Conclusion
10. MLN*
Syntax: a set of weighted logical rules
0.5 Smokes(p) => Cancer(p)
// if you smoke, you are more likely to have cancer
Weights: cost for rule violation
Semantics: a distribution over possible worlds
Each possible world I incurs total cost cost(I)
Pr[I] ∝exp(−cost(I))
Thus most likely world has lowest cost
4
* [Richardson & Domingos 2006]
http://hazy.cs.wisc.edu/hazy/papers/tuffy-vldb2011-slides.pdf
MLN - Choice of Implementation - To GUI or Not to GUI - Conclusion
12. MLN*
5
Rules!
0.5 Smokes(p) => Cancer(p)
// if you smoke, you are more likely to have cancer
0.4 Friends(p1,p2) ∧ Smokes(p1) => Smokes(p2)
0.4 Friends(p1,p2) ∧ Smokes(p2) => Smokes(p1)
// friends that smoke are more likely to have friends that also smoke
* http://hazy.cs.wisc.edu/hazy/papers/tuffy-vldb2011-slides.pdf
MLN - Choice of Implementation - To GUI or Not to GUI - Conclusion
13. MLN*
5
Rules!
0.5 Smokes(p) => Cancer(p)
// if you smoke, you are more likely to have cancer
0.4 Friends(p1,p2) ∧ Smokes(p1) => Smokes(p2)
0.4 Friends(p1,p2) ∧ Smokes(p2) => Smokes(p1)
// friends that smoke are more likely to have friends that also smoke
* http://hazy.cs.wisc.edu/hazy/papers/tuffy-vldb2011-slides.pdf
Certain!
Friends(Anna,Bob)
Smokes(Anna)
MLN - Choice of Implementation - To GUI or Not to GUI - Conclusion
14. MLN*
5
Rules!
0.5 Smokes(p) => Cancer(p)
// if you smoke, you are more likely to have cancer
0.4 Friends(p1,p2) ∧ Smokes(p1) => Smokes(p2)
0.4 Friends(p1,p2) ∧ Smokes(p2) => Smokes(p1)
// friends that smoke are more likely to have friends that also smoke
* http://hazy.cs.wisc.edu/hazy/papers/tuffy-vldb2011-slides.pdf
Certain!
Friends(Anna,Bob)
Smokes(Anna)
Uncertain!
Cancer(?)
MLN - Choice of Implementation - To GUI or Not to GUI - Conclusion
36. Conclusion
Pros
Easy-to-use tool for MLN
Dynamic search of predicates, rules, and evidence
Add/remove features for predicates, rules, and evidence
Facilitates new parameters available in future versions of Tuffy
19MLN - Choice of Implementation - To GUI or Not to GUI - Conclusion
37. Conclusion
Pros
Easy-to-use tool for MLN
Dynamic search of predicates, rules, and evidence
Add/remove features for predicates, rules, and evidence
Facilitates new parameters available in future versions of Tuffy
Cons
Still a beta tool
Needs more serious testing
A lot more GUI features could be incorporated
19MLN - Choice of Implementation - To GUI or Not to GUI - Conclusion